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Autor:
Levy, Omer; Dagan, Ido; Stanovsky, Gabriel; Eckle-Kohler, Judith; Gurevych, Iryna:

Titel:
Modeling extractive sentence intersection via subtree entailment

Quelle:
In: The COLING 2016 Organizing Committee (Hrsg.): Proceedings of the 26th International Conference on Computational Linguistics (COLING) Osaka : The COLING 2016 Organizing Committee (2016) , 2891-2901

URL des Volltextes:
http://www.aclweb.org/anthology/C/C16/C16-1272.pdf

Sprache:
Englisch

Dokumenttyp:
4. Beiträge in Sammelwerken; Tagungsband/Konferenzbeitrag/Proceedings

Schlagwörter:
Algorithmus, Computerlinguistik, Daten, Klassifikation, Semantik, Struktur, Syntax, Text


Abstract(englisch):
Sentence intersection captures the semantic overlap of two texts, generalizing over paradigms such as textual entailment and semantic text similarity. Despite its modeling power, it has received little attention because it is difficult for non-experts to annotate. We analyze 200 pairs of similar sentences and identify several underlying properties of sentence intersection. We leverage these insights to design an algorithm that decomposes the sentence intersection task into several simpler annotation tasks, facilitating the construction of a high quality dataset via crowdsourcing. We implement this approach and provide an annotated dataset of 1,764 sentence intersections. (DIPF/Orig.)


DIPF-Abteilung:
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last modified Nov 11, 2016